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» Supervised probabilistic principal component analysis
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MICCAI
2009
Springer
14 years 8 months ago
Building Shape Models from Lousy Data
Statistical shape models have gained widespread use in medical image analysis. In order for such models to be statistically meaningful, a large number of data sets have to be inclu...
Marcel Lüthi, Thomas Albrecht, Thomas Vetter
CVPR
2007
IEEE
14 years 9 months ago
Recognizing Human Activities from Silhouettes: Motion Subspace and Factorial Discriminative Graphical Model
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
Liang Wang, David Suter
ICIAP
2003
ACM
14 years 27 days ago
Multi-block PCA method for image change detection
Principal component analyses (PCA) has been widely used in reduction of the dimensionality of datasets, classification, feature extraction, etc. It has been combined with many oth...
B. Qiu, Véronique Prinet, Edith Perrier, Ol...
PAMI
2008
231views more  PAMI 2008»
13 years 7 months ago
Nonrigid Structure-from-Motion: Estimating Shape and Motion with Hierarchical Priors
This paper describes methods for recovering time-varying shape and motion of nonrigid 3D objects from uncalibrated 2D point tracks. For example, given a video recording of a talkin...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
ECCV
2004
Springer
14 years 9 months ago
3D Human Body Tracking Using Deterministic Temporal Motion Models
Abstract. There has been much effort invested in increasing the robustness of human body tracking by incorporating motion models. Most approaches are probabilistic in nature and se...
Raquel Urtasun, Pascal Fua